Friday, September 27, 2013

Low-fat chocolate milk consumption has been suggested as an effective strategy to speed up recovery after exercise. However, not all studies have shown a positive effect following chocolate milk consumption and this should be taken into consideration when applying these findings. For a comprehensive review you can read the article by Spaccarotella and Andzel

Thursday, September 12, 2013

Are you keen in learning keys for success from Sir Alex Ferguson? In this October’s edition of the Harvard Business Reviews Professor Anita Elberse and Sir Alex Ferguson collaborated to summarize key strategies to Ferguson’s successful career. These approaches apply to other places and life conditions. For me, it was an exciting time to read this paper. I have learned a lot.

Wednesday, September 11, 2013

Warren Young and Nathan Rogers from Australia investigated the effect of two different training methods on planned and reactive agility tests. Although the data are on Australian rules players, I think they apply also to football (soccer).

This study examined the effects of overnight sleep deprivation on recovery following competitive rugby league matches.Eleven male, amateur rugby league players performed two competitive matches, followed by either a normal night's sleep (~8h; CONT) or a sleep deprived night (~0h; SDEP) in a randomised fashion. Testing was conducted the morning of the match, and immediately post-match, 2h post and the next morning (16h post-match). Measures included counter-movement jump (CMJ) distance, knee extensor maximal voluntary contraction (MVC), voluntary activation (VA), venous blood creatine kinase (CK) and C-reactive protein (CRP), perceived muscle soreness and a word-colour recognition cognitive function test. Percent change between post- and 16h post-match was reported to determine the effect of the intervention the next morning.Large effects indicated a greater post- to 16h post-match percentage decline in CMJ distance following SDEP compared to CONT (P=0.10-0.16; d=0.95-1.05). Similarly, the percentage decline in incongruent word-colour reaction times were increased in SDEP trials (P=0.007; d=1.75). Further, large effects indicated higher CK and CRP responses 16h post-match during SDEP compared to CONT (P=0.11-0.87; d=0.80-0.88).

Conclusion

Sleep deprivation negatively affected recovery following a rugby league match, specifically impairing CMJ distance and cognitive function. Practitioners should promote adequate post-match sleep patterns or adjust training demands the next day to accommodate the altered physical and cognitive state following sleep deprivation.

The aim of this study was to evaluate the effectiveness of different recovery strategies on repeat cycling performance where a short duration between exercise bouts is required. Eleven highly-trained cyclists (mean ± SD; age = 31 ± 6 years; mass = 74.6 ± 10.6 kg; height = 180.5 ± 8.1 cm) completed four trials each consisting of three 30 s maximal sprints (S1, S2, S3) on a cycle ergometer, separated by a 20-min recovery period. In a counter-balanced, cross-over design, each trial involved subjects performing one of four different recovery strategies; compression garments (COMP), electro-muscle stimulation (EMS), humidification therapy (HUM) and a passive control (CON). The sprint tests implemented a 60 s pre-load (at an intensity of 4.5 W·kg-1) prior to a 30 s maximal sprint. Mean power output (Watts) for the three sprints, in combination with perceived recovery and blood lactate concentration were used to examine the effect of each recovery strategy. In CON, S2 and S3 were (mean ± SD): -2.1 ± 3.9% and -3.1 ± 4.2% lower than S1. Compared to CON, COMP resulted in a higher mean power output from S1 to S2 (mean ±90%CL: 0.8 ±1.2%; possibly beneficial) and S1 to S3 (1.2 ±1.9%; possibly beneficial); whilst HUM showed a higher mean power output from S1 to S3 (2.2 ±2.5%; likely beneficial) relative to the CON.

Conclusion

We would suggest that both compression garments and humidification therapy may be effective strategies to enhance recovery between repeated sprint cycling bouts separated by ~30min.

The aim of the present study was to 1) examine the magnitude of between-GPS model differences in commonly reported running-based measures in football, 2) examine between-unit variability and 3) assess the effect of software updates on these measures. Fifty identical brand GPS units (15 SPI-proX and 35 SPI-proX2, 15 Hz, GPSports, Canberra, Australia) were attached to a custom-made plastic sled towed by a player performing simulated match running activities. GPS data collected during training sessions over 4 weeks from 4 professional football players (n = 53 files) were also analyzed before and after 2 manufacturer-supplied software updates. There were substantial differences between the different models (e.g., standardized difference for the number of acceleration >4 m.s-2 = 2.1; 90% confidence limits (1.4, 2.7), with 100% chance of a true difference). Between-unit variations ranged from 1% (maximal speed) to 56% (number of deceleration >4 m.s-2). Some GPS units measured 2 to 6 times more acceleration/deceleration occurrences than others. Software updates did not substantially affect the distance covered at different speeds or peak speed reached, but one of the updates led to large and small decreases in the occurrence of accelerations (-1.24;-1.32,-1.15) and decelerations (-0.45; -0.48,-0.41), respectively.

Conclusion

Practitioners are advised to apply care when comparing data collected with different models or units, or when updating their software. The metrics of accelerations and decelerations show the most variability in GPS monitoring and must be interpreted cautiously.

Department of Sport and Exercise Sciences, University of Sunderland, UK

The aim of this study was to compare the match performance and physical capacity of players in the top three competitive standards of English soccer. Match performance data were collected from players in the FA Premier League (n=190), Championship (n=155) and League 1 (n=366) using a multiple-camera system. In addition, a selection of players from the Premier League (n=56), Championship (n=61) and League 1 (n=32) performed the Yo-Yo intermittent endurance test level 2 (Yo-Yo IE2) to determine physical capacity. Players in League 1 and the Championship performed more (p<.01) high-intensity running than those in the Premier League (Effect Size [ES]: 0.4-1.0). Technical indicators such as pass completion, frequency of forward and total passes, balls received and average touches per possession were 4-39% higher (p<.01) in the Premier League compared to lower standards (ES: 0.3-0.6). Players also covered more (p<.05) high-intensity running when moving down (n=20) from the Premier League to the Championship (ES: 0.4) but not when players moved up (n=18) standards (ES: 0.2). Similar Yo-Yo IE2 test performances were observed in Premier League, Championship and League 1 players (ES: 0.2-0.3). Large magnitude relationships (p<.05) were observed between Yo-Yo IE2 test performances and the total and high-intensity running distance covered in both Championship (r=.56 and .64) and Premier League matches (r=.61 and .54).

Conclusion

The data demonstrate that high-intensity running distance was greater in players at lower compared to higher competitive standards despite a similar physical capacity in a subsample of players in each standard. These findings could be associated with technical characteristics inherent to lower standards that require players to tax their physical capacity to a greater extent but additional research is still required to confirm these findings.